The present application relates generally to an improved data processing apparatus and method and more specifically to mechanisms for performing concept analysis operations utilizing accelerators.
Everyday life is dominated by information technology and systems for obtaining information and knowledge from collections of data. For example, search engines operate on large collections of data to obtain information related to a search query. Question and Answer (QA) systems, such as the IBM Watson™ QA system available from International Business Machines (IBM) Corporation of Armonk, N.Y., operate on a corpus of documents or other portions of information to answer natural language questions. Moreover, many social networking services represent their users, communications, and the like, as large data sets. Many times it is important to perform knowledge extraction, reasoning, and various other analytics on these large scale data sets so as to facilitate the operation of the systems, e.g., answer questions, return search results, or provide functionality within the social networking services. For example, many social networking services help individuals identify other registered users that they may know or have a connection with. Such functionality requires analyzing a large set of data representing the users of the social networking service.
In facilitating searching of information in large sets of documents, such as searches of the web pages on the Internet (or the “web”), search engines are employed which rank results based on various factors. One such search engine is the Google™ search engine which uses a ranking algorithm referred to as “PageRank.” PageRank exploits the linkage structure of the web to compute global “importance” scores that can be used to influence the ranking of search results.
Recently, an effort at Stanford University, as part of their Stanford Global Infobase Project, has developed an algorithm for allowing users to define their own notion of importance for each individual query. This algorithm, referred to as personalized PageRank, provides online personalized web searching with personalized variants of PageRank based on a private, personalized profile.